Many of today's hydrocarbon reservoirs were formed by the sedimentary depositions of fluid flows in ancient basins. The fluid flows transported the sediment, sorting and selectively depositing differently-sized grains to form sedimentary bodies with predictable geometries and properties. If such processes can be feasibly simulated with sufficient accuracy, realistic modeling of subsurface reservoirs becomes possible. The oil and gas industry desires geologic models as input to reservoir performance simulations which are used to select locations for new wells, estimate hydrocarbon reserves, and plan reservoir-development strategies. Geologic models specify key parameters (such as fluid properties and the spatial distribution of permeability) for characterizing reservoir performance, and determining the producibility of the reservoir. (For sandstone reservoirs, the spatial distribution of permeability is a function of the grain-size distribution of sands which compose the reservoir, the compartmentalization of those sands by barriers of finer grained material, and the mineralogy and burial history of the reservoir.) Models that are more realistic enable the industry to formulate more optimal production strategies
The geologic modeling process can use many different types of measurement data, including but not limited to rock-property data obtained from cores, well logs, seismic data, well test and production data, and structural and stratigraphic surfaces that define distinct zones within the model space. Typically, the resolution or spatial coverage of the available measurement data is not adequate to uniquely determine the rock properties at every point in the geologic model space. Accordingly, the industry has formulated a number of approaches to filling in the missing data, including simulation of the sediment transport and deposition processes.
Such process simulation has been attempted in various ways, including: solving full 3D fluid flow equations; using reduced physics strategies and solving a set of much simpler phenomenological equations, and solving a set of 2D depth-averaged flow equations. When attempted on useful space and time resolutions at the scale of an entire reservoir and/or basin, full 3D fluid flow simulations are computationally prohibitive. The reduced physics strategies employ heuristic rules or random-walk processes to simulate sediment transport, but suffer from artifacts and numerical noise levels that limit their utility. The existing depth-averaged flow simulations may employ the classic St. Venant shallow water equations or Parker's three or four-equation turbidity current model to gain, relative to the full 3D fluid flow simulations, a significant computational advantage.
For this reason, simulations using 2D depth-averaged flow equations are widely used in many engineering applications. Yet, in the context of reservoir and/or basin modeling, many of the natural flows are highly stratified, and the degree of the stratification changes dynamically in time and space. Moreover, such stratification is a key influence on the final geometries and properties of the deposited materials. For example, the stratification of the suspended muddy materials in the flow is closely associated with the features of levee and argillaceous deposits. In existing depth-averaged flow simulation of reservoir and/or basins, the loss of flow and sediment concentration variability in the vertical direction, and their corresponding changes in time and space is expected to result in significant errors.